The present application relates to the field of x-ray and computed tomography (CT). It finds particular application with the use of medical imaging apparatuses that comprise energy resolving detectors. It also relates to security applications and other applications where obtaining information about the energy spectra of detected radiation would be useful.
CT and other radiographic imaging systems are useful to provide information, or rather images, of interior aspects of an object. Generally, the object is exposed to radiation, and an image is formed based upon the radiation absorbed by the interior aspects of the object, or rather an amount of radiation that is able to pass through the object. Highly dense aspects of the object absorb more radiation than less dense aspects, and thus an aspect having a higher density, such as a bone or mass, for example, will be apparent when surrounded by less dense aspects, such as fat tissue or muscle.
The detectors of a radiographic imaging system are configured to convert the radiographic energy that has traversed the object into signals and/or data that may be processed to produce the images. There are numerous detectors that may be utilized depending upon count rates and/or the system's intended application (e.g., medical, security, etc.), for example.
Energy resolving detectors (e.g., photon counting detectors) are used on some radiographic imaging systems, particularly in nuclear medicine applications. Such detectors are comprised of a plurality of pixels that are configured to detect photon strikes, or rather energy transferred to the detector when a photon strike occurs. When a photon strike occurs, the pixel generates a pulse indicative of the photon. Generally, the pulse includes a fast-rising portion followed by a slower decay portion. The generated pulse is then processed, along with other pulses related to other photon strikes, to generate an image of the object under examination.
Energy resolving detectors have numerous benefits over conventional x-ray and CT detectors. For example, energy resolving detectors have a relatively greater sensitivity because the photons comprised within the radiation are counted. Additionally, such detectors are able to provide information about the energy spectra of detected radiation.
While energy resolving detectors have proven useful in a variety of applications, several drawbacks have limited further adoption of these detectors. One of the drawbacks is a phenomenon known as pulse pile-up. Pulse pile-up occurs when two photons strike a pixel in close temporal proximity, causing the pulse of the first photon strike to be combined with the pulse of the second photon strike because the first pulse does not have time to decay before the second photon strike. Thus, a pulse generated from the second photon strike effectively just extends the first pulse. Because the pulse of the second photon strike is combined with the pulse of the first photon strike, the system mistakes the event as a single photon strike. In doing so, the system may mischaracterize the first photon (e.g., assigning it a higher energy spectrum than it actually had) and may not recognize the second photon. Pulse pile-up is of particular concern in CT and x-ray applications that have a relatively high photon count rate because of the increased probability that two photons will strike the same pixel in close temporal proximity.
A second drawback of energy resolving detectors is known as charge sharing. Charge sharing occurs when two or more adjacent pixels generate pulses related to the same photon strike. This generally occurs when the photon strike occurs near the edge of a pixel, and a portion of the charge cloud created by the strike intrudes onto a second pixel (e.g., making it appear as if a separate photon strike has occurred on the second pixel). Since adjacent pixels appear to have endured respective photon strikes, they generate separate pulses, which may mistakenly be interpreted as two or more separate strikes (e.g., instead of a single strike from a (higher energy) photon). Additionally, the system may mischaracterize the photon since the charge is shared amongst two or more pixels (e.g., assigning it a lower energy spectrum than it actually had). To correct for charge sharing, statistical analysis techniques have been used. While such techniques have proven effective at high count rates, at lower count rates, the statistical techniques are less effective because there are fewer photons for the analysis.